Humans are inquisitive and social creatures. Accordingly, many computer applications have been developed with social features allowing users the ability to interact just as humans might in a face-to-face setting, such as allowing people to make recommendations to one another. For example, some websites have been developed with a primary focus upon user recommendations (e.g., restaurant review sites, video game reviews, business reviews) and others have a different focus but similarly allow for user recommendations (e.g., online storefronts allowing reviews of items for sale, social networking systems). Such recommendations are often in the form of a numeric rating and/or a textual description (i.e., “review”) of a particular thing or “entity.”
However, many of these applications suffer because the quality of the reviews is highly questionable, leading the usefulness of the reviews to be significantly degraded. For example, some reviewers posting reviews may not have actually interacted with the entity being reviewed. Additionally, some reviewers may be biased and thus have a strong positive or negative predispositions (e.g., an affinity for a particular brand of cola) that affect the objectivity of their reviews. Further, some reviews may be fraudulent, such as where a user is paid or encouraged to submit a positive or negative review. Reviews may also be poor when they are out-of-date and relate to an entity different than how it currently exists, such as a review for an early, buggy release of software that has subsequently been fixed or a restaurant on its opening night. Moreover, many reviews come from users having atypically positive or negative experiences with an entity, and thus the results will be highly skewed, as users with middle-of-the-road opinions may not be motivated to share their thoughts.